Enhancing the Effectiveness of Community Health Workers to Reduce Cervical Cancer Disparities in African American Women

项目总结/摘要 非裔美国妇女被诊断为宫颈癌（CC）的可能性几乎是白色的两倍 妇女他们最初的临床表现也更消极，其特征是更严重的发育异常变化， 晚期疾病。考虑到这一点，黑人女性的死亡率也是男性的两倍多， 与白色女性相比，更糟糕的是，无论肿瘤分期如何，这些生存差异都持续存在 初步诊断。不一定非要这样。CC是完全可以预防的。 广泛接受HPV疫苗接种和遵守宫颈筛查指南（并进行适当的随访） 几乎可以消除所有新的CC病例。不幸的是，只有42%的年轻成年黑人妇女 至少接种过一剂HPV疫苗的女性比例为52%，而白色女性为52%。校正自报数据 显示只有58%的黑人妇女遵守筛查指南，而白色妇女的这一比例为73%。 在以前的试点工作中，我们开发和测试了一个移动的CC导航干预非洲裔美国人 妇女一个基于网络的综合风险评估允许我们的短信软件应用程序从一个库中选择 针对每个用户的特定宫颈健康预防专门定制的视频和基于文本的消息 挑战该原型包括3种类型的视频（脚本小插曲，无脚本的同行叙述， 教育指导）和3种类型的文本消息（提醒、教育和支持）。可用性测试 强烈支持这种面向患者的干预措施的可行性和潜在有效性。 我们建议在此试点工作的基础上开发一个数字仪表板， 移动的导航干预和电子健康记录（EHR）。该综合包将用于 提供导航服务的社区卫生工作者（CHW）。这个新的分析工具将提供CHW 在患者层面、病例层面和就诊层面实时提供导航数据的统一图形视图， 水平所有导航数据都将依靠各种图形元素以视觉方式呈现。 我们将招募16名目标终端用户，他们提供一系列的癌症预防导航服务， 参加焦点小组的工作场所设置。参与者将被要求判断布局的适当性， 计划仪表板的结构和功能。此外，我们将招聘行政领导，董事， 实施/项目经理以及拥有上游或下游接触点的最终用户， 个人访谈的电子健康记录工作流程（共计N=12）。这些讨论将侧重于挑战和 将拟议的mHealth工具整合到EHR工作流程中的机会。基于我们从 这些团体和我们的专家顾问团队，我们将开发一个原型仪表板。当 完成后，16个目标最终用户将返回进行可用性测试。可用性测试将涉及完成一个 一系列任务，旨在模拟典型的最终用户将如何体验 开发的dashboard将评估三个可用性指标：效率、准确性和主观满意度。

PROJECT SUMMARY/ABSTRACT African American women are almost twice as likely to be diagnosed with cervical cancer (CC) as white women. Their initial clinical picture is also more negative, characterized by more severe dysplastic changes and later-stage disease. Given this, it is not surprising that Black women are also more than twice as likely to die from CC as compared to white women. Even worse, these survival disparities persist irrespective of tumor stage at initial diagnosis. It does not have to be this way. CC is completely preventable. Broad uptake of HPV vaccination and adherence to cervical screening guidelines (with proper follow-up) would virtually eliminate all new cases of CC. Unfortunately, only 42% of young adult Black women have received at least one dose of the HPV vaccine compared to 52% of white women. Corrected self-report data show that only 58% of Black women are adherent to screening guidelines compared to 73% of white women. In previous pilot work, we developed and tested a mobile CC navigation intervention for African American women. An integrated web-based risk assessment allowed our SMS software app to select from a library of videos and text-based messages specifically tailored for each user’s particular cervical health prevention challenges. This prototype included 3 types of videos (scripted vignettes, unscripted peer narratives, and educational instruction) and 3 types of text messages (reminder, educational, and supportive). Usability testing strongly supported the feasibility and potential effectiveness of this patient-facing intervention. We are proposing to build on this pilot work by developing a digital dashboard that integrates with our mobile navigation intervention and with electronic health records (EHR). This integrated package will be for community health workers (CHWs) who provide navigation services. This new analytic tool will provide CHWs a unified, graphical view of their navigation data in real-time at the patient-level, case-level, and encounter- level. All navigation data will be presented visually, relying on a diverse array of graphical elements. We will recruit 16 target end-users who provide cancer prevention navigation services in a range of workplace settings to participate in focus groups. Participants will be asked to judge the adequacy of the layout, structure, and functionality of the planned dashboard. In addition, we will recruit executive leaders, directors, implementation/project managers, and end users who have either upstream or downstream touch points with EHR workflows for individual interviews (total N=12). These discussions will focus on the challenges and opportunities of integrating the proposed mHealth tools into EHR workflows. Based on what we learn from these groups and our expert team of consultants, we will then develop a prototype dashboard. When completed, the 16 target end-users will return for usability testing. The usability test will involve completing a series of tasks intended to simulate how a typical end-user would experience the functionality of the fully developed dashboard. Three usability metrics will be assessed: efficiency, accuracy, and subjective satisfaction.